Abstract: We study the distributed allocation of tasks to cooperating robots in real
time, where each task has to be assigned to exactly one robot so that the sum
of the latencies of all tasks is as small as possible. We propose a new
auction-like algorithm, called Sequential Incremental-Value (SIV) auction,
which assigns tasks to robots in multiple rounds. The idea behind SIV auctions
is to assign as many tasks per round to robots as possible as long as their
individual costs for performing these tasks are at most a given bound, which
increases exponentially from round to round. Our theoretical results show that
the team costs of SIV auctions are at most a constant factor larger than
minimal.

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